LAQV/REQUIMTE, Departamento de Ciências Químicas, Laboratório de Bromatologia e Hidrologia, Faculdade de Farmácia , Universidade do Porto , Rua de Jorge Viterbo Ferreira n.° 228 , 4050-313 Porto , Portugal.
Chair of Brewing and Beverage Technology , Technische Universität München , Weihenstephaner Steig 20 , 85354 Freising , Germany.
J Agric Food Chem. 2020 Feb 19;68(7):2155-2163. doi: 10.1021/acs.jafc.9b06139. Epub 2020 Feb 7.
Mandarina Bavaria is a "Special Flavor" hop variety, described as fruity, with pronounced mandarin and citrus, combined with traditional hoppy sensations. The relationship between fruity-citrus intensity and the volatile profile of dry-hopped beers was assessed in order to predict the sensory perception of those dry-hopped beers using the content of selected volatile compounds. For this purpose, two base beers (A and B) that presented statistical differences ( < 0.05) in the composition of volatile compounds and on the sensory perception were dry hopped with 3 g/L Mandarina Bavaria hop. Twenty-four volatiles from hop were quantified during 15 days of dry hopping, while the sensory perception was followed by a certified trained panel. The sensory perception of total hoppy content (in a scale from 0 to 5) can be estimated using a PLS equation ( = 0.654): total hoppy = 1.8 + [myrcene (μg/L) × 7.5 × 10] + [2-methylbutyl-2-methylpropanoate (μg/L) × 4.2 × 10] + [linalool (μg/L) × 7.2 × 10] + [α-humulene (μg/L) × 2.3 × 10]). Successful models were also obtained to predict citrus ( = 0.745), green fruit ( = 0.598), and sweet fruit ( = 0.626) characteristics of dry-hopped beers.
曼达琳娜巴伐利亚（Mandarina Bavaria）是一种“特殊风味”啤酒花品种，具有水果味，带有明显的柑橘和橘子味，与传统的啤酒花味道相结合。为了评估水果-柑橘强度与干投啤酒挥发性特征之间的关系，以便使用选定挥发性化合物的含量预测那些干投啤酒的感官感知，研究人员评估了水果-柑橘强度与干投啤酒挥发性特征之间的关系。为此，研究人员使用 3 g/L 的曼达琳娜巴伐利亚啤酒花对两种基础啤酒（A 和 B）进行了干投，这两种基础啤酒在挥发性化合物的组成和感官感知方面存在统计学差异（<0.05）。在 15 天的干投过程中，从啤酒花中定量了 24 种挥发性物质，同时由经过认证的训练有素的小组跟踪感官感知。使用 PLS 方程（=0.654）可以估计总啤酒花含量（0 到 5 的比例）的感官感知：总啤酒花=1.8+[迷迭香（μg/L）×7.5×10]+[2-甲基丁基-2-甲基丙酸酯（μg/L）×4.2×10]+[芳樟醇（μg/L）×7.2×10]+[α-葎草烯（μg/L）×2.3×10]）。还成功获得了预测干投啤酒柑橘（=0.745）、绿色水果（=0.598）和甜水果（=0.626）特征的模型。
